Building Accessible AI Applications with Voice

Voice technology is essential for accessibility. Here's how to build inclusive AI applications.

Why Voice Matters for Accessibility

• 1.3 billion people have visual impairments
• Voice enables hands-free usage
• Natural interface for all users
• Required for many enterprise applications

Accessibility Use Cases

Screen Reader Enhancement

Replace robotic voices with natural AI voices:

from langvoice_sdk import LangVoiceClient

client = LangVoiceClient(api_key="your-key")

# Convert any text to natural speech
audio = client.generate(
    text=webpage_content,
    voice="emma",  # Clear, natural voice
    speed=1.0  # Adjustable speed
)

Document to Audio

Make documents accessible as audio:

# Convert PDF/DOC to spoken audio
text = extract_text(document)
audio = client.generate(text=text, voice="heart")

Real-Time Assistance

Voice responses for blind users:

# AI assistant that speaks responses
response = ai.generate(user_query)
audio = langvoice.generate(text=response, voice="michael")
play_audio(audio)

Best Practices

1. Clear Voices: Use articulate voices like Emma, Michael
2. Speed Control: Let users adjust playback speed
3. Alt Text: Always provide text alternatives
4. Multi-Language: Support diverse users

Compliance Considerations

• WCAG 2.1 guidelines
• Section 508 (US)
• EN 301 549 (EU)

Make your AI accessible with LangVoice's natural voices!